> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Condition with list of steps

> Pass a list of steps to a Condition so one check can trigger a whole sequence.

A `Condition` can run a single step or a whole list of them. Here, two conditions sit
inside a `Parallel` block: one triggers a single research step and the other runs a
three-step analysis sequence.

**When to use**: A boolean check that should gate several sequential steps as one branch.

Install dependencies:

```shell theme={null}
uv pip install agno openai exa-py
export EXA_API_KEY=***
```

```python condition_with_list_of_steps.py theme={null}
from agno.agent.agent import Agent
from agno.tools.hackernews import HackerNewsTools
from agno.tools.exa import ExaTools
from agno.workflow.condition import Condition
from agno.workflow.parallel import Parallel
from agno.workflow.step import Step
from agno.workflow.types import StepInput
from agno.workflow.workflow import Workflow

# === AGENTS ===
hackernews_agent = Agent(
    name="HackerNews Researcher",
    instructions="Research tech news and trends from Hacker News",
    tools=[HackerNewsTools()],
)

exa_agent = Agent(
    name="Exa Search Researcher",
    instructions="Research the topic using Exa search.",
    tools=[ExaTools()],
)

content_agent = Agent(
    name="Content Creator",
    instructions="Create well-structured content from research data",
)

# Additional agents for multi-step condition
trend_analyzer_agent = Agent(
    name="Trend Analyzer",
    instructions="Analyze trends and patterns from research data",
)

fact_checker_agent = Agent(
    name="Fact Checker",
    instructions="Verify facts and cross-reference information",
)

# === RESEARCH STEPS ===
research_hackernews_step = Step(
    name="ResearchHackerNews",
    description="Research tech news from Hacker News",
    agent=hackernews_agent,
)

# === MULTI-STEP CONDITION STEPS ===
deep_exa_analysis_step = Step(
    name="DeepExaAnalysis",
    description="Conduct deep research with Exa search",
    agent=exa_agent,
)

trend_analysis_step = Step(
    name="TrendAnalysis",
    description="Analyze trends and patterns from the research data",
    agent=trend_analyzer_agent,
)

fact_verification_step = Step(
    name="FactVerification",
    description="Verify facts and cross-reference information",
    agent=fact_checker_agent,
)

# === FINAL STEPS ===
write_step = Step(
    name="WriteContent",
    description="Write the final content based on research",
    agent=content_agent,
)


# === CONDITION EVALUATORS ===
def check_if_we_should_search_hn(step_input: StepInput) -> bool:
    """Check if we should search Hacker News"""
    topic = step_input.input or step_input.previous_step_content or ""
    tech_keywords = [
        "ai",
        "machine learning",
        "programming",
        "software",
        "tech",
        "startup",
        "coding",
    ]
    return any(keyword in topic.lower() for keyword in tech_keywords)


def check_if_comprehensive_research_needed(step_input: StepInput) -> bool:
    """Check if comprehensive multi-step research is needed"""
    topic = step_input.input or step_input.previous_step_content or ""
    comprehensive_keywords = [
        "comprehensive",
        "detailed",
        "thorough",
        "in-depth",
        "complete analysis",
        "full report",
        "extensive research",
    ]
    return any(keyword in topic.lower() for keyword in comprehensive_keywords)


if __name__ == "__main__":
    workflow = Workflow(
        name="Conditional Workflow with Multi-Step Condition",
        steps=[
            Parallel(
                Condition(
                    name="HackerNewsCondition",
                    description="Check if we should search Hacker News for tech topics",
                    evaluator=check_if_we_should_search_hn,
                    steps=[research_hackernews_step],  # Single step
                ),
                Condition(
                    name="ComprehensiveResearchCondition",
                    description="Check if comprehensive multi-step research is needed",
                    evaluator=check_if_comprehensive_research_needed,
                    steps=[  # Multiple steps
                        deep_exa_analysis_step,
                        trend_analysis_step,
                        fact_verification_step,
                    ],
                ),
                name="ConditionalResearch",
                description="Run conditional research steps in parallel",
            ),
            write_step,
        ],
    )

    try:
        workflow.print_response(
            input="Comprehensive analysis of climate change research",
            stream=True,
        )
    except Exception as e:
        print(f"Error: {e}")
    print()
```